What does it really take to make data usable—not just technically FAIR, but truly findable, accessible, interoperable, and reusable in the ways science needs today?
In this episode of The FAIR² Chronicles, we explore the frustrating reality of pseudo-FAIR data and the critical gap between aspiration and implementation. We introduce FAIR² as a powerful framework that embeds context, clarity, and computability into the data lifecycle—from rich metadata and semantic alignment to transparent workflows and reproducibility tools.
Whether you’re a researcher, funder, policymaker, or data steward, this conversation will help you rethink what it means to share data that’s not just open, but trustworthy, understandable, and ready to drive discovery.
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